Changting Shi

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About

Changting Shi is a leading researcher in autonomous marine robotics, with a primary focus on unmanned surface vehicles (USVs) and multi-robot systems. Their most influential work, "An adaptive obstacle avoidance algorithm for unmanned surface vehicle in complicated marine environments" (52 citations), addresses the fundamental challenge of safe navigation in dynamic and unpredictable waters, proposing an adaptive algorithm that enables USVs to autonomously avoid obstacles in real time. This contribution is critical for advancing the practical deployment of USVs in surveillance, environmental monitoring, and search-and-rescue missions. Earlier, Shi contributed to the field of multi-robot coordination with "Formation Control of Multiple Behavior-based robots" (20 citations), introducing a behavior-based, leader-referenced approach that uses a dynamic-dead-zone method to maintain formation while ensuring flexibility and responsiveness. More recently, Shi developed a method to evaluate autonomous performance in USVs (2016), focusing on adjustable autonomy—a mechanism that balances human-operator control with machine independence to improve mission efficiency. Through these works, Shi has helped lay the groundwork for more intelligent, reliable, and cooperative autonomous systems in complex marine environments.